import cv2
import math
import numpy as np
import matplotlib.pyplot as plt
import random
from sklearn.cluster import KMeans
'''helper function to display images'''
def display_images(images,titles,row,col):
fig = plt.figure(figsize = (20,20))
for i in range(len(images)):
fig.add_subplot(row,col,i + 1)
#RGB
if np.ndim(images[i]) == 3:
plt.imshow(images[i])
else:
plt.imshow(images[i],cmap = 'gray')
plt.title(titles[i])
plt.axis("off")
''' function load a input image,flash image,trimap h for an image and display the images '''
def load_images(index):
f0 = cv2.imread("./../data_3/" + str(index) + "/noflash.png",cv2.IMREAD_UNCHANGED)
f1 = cv2.imread("./../data_3/" + str(index) + "/flash.png",cv2.IMREAD_UNCHANGED)
tm = cv2.imread("./../data_3/" + str(index) + "/trimap.png",cv2.IMREAD_UNCHANGED)
#print(im.shape,fl.shape,tr.shape)
f0 = cv2.cvtColor(f0,cv2.COLOR_BGR2RGB)
f1 = cv2.cvtColor(f1,cv2.COLOR_BGR2RGB)
f2 = f1 - f0
#print(f0.shape,f1.shape,f2.shape,tm.shape)
display_images([f0,f1,f2,tm],["no flash","flash","only flash","trimap"],2,2)
return f0,f1,f2,tm
''' helper function to divide the trimap into surely foreground and surely background and unknown region'''
def get_maps(trimap):
bg = np.copy(trimap.astype(np.uint8))
fg = np.copy(trimap.astype(np.uint8))
un = np.copy(trimap.astype(np.uint8))
bg[trimap != 0] = 0
bg[trimap == 0] = 255
fg[trimap != 255] = 0
un[trimap == 125] = 255
un[trimap != 125] = 0
return bg,fg,un
''' helper to zero pad the image '''
def pad_image(img,pad_x,pad_y):
#grayscale
if(np.ndim(img) == 2):
(l,b) = img.shape
new_image = np.zeros((l + 2 * pad_y, b + 2 * pad_x),dtype = np.uint8)
new_image[pad_y : pad_y + l,pad_x : pad_x + b] = img
return new_image
#RGB
else:
(l,b,h) = img.shape
new_image = np.zeros((l + 2 * pad_y, b + 2 * pad_x , h),dtype = np.uint8)
new_image[pad_y : pad_y + l,pad_x : pad_x + b,:] = img
return new_image
''' create a gaussian kernel of size k with sigma '''
def create_gaussian(k,sigma):
return np.dot(cv2.getGaussianKernel(k,sigma),cv2.getGaussianKernel(k,sigma).T)
''' helper function to get neighbourhood '''
''' assuming the height and width to be odd for convenience'''
''' to do handle exceptions for now assuming its correct'''
def get_neighbourhood(img,centre_y,centre_x,height ,width ):
new_centre_y = centre_y + height // 2
new_centre_x = centre_x + width // 2
''' grayscale'''
#print(np.ndim(img))
if(np.ndim(img) == 2):
pad_x = width // 2
pad_y = height // 2
padded_img = pad_image(img,pad_x,pad_y)
(l,b) = img.shape
left = new_centre_x - width // 2
right = new_centre_x + width // 2
up = new_centre_y - height // 2
down = new_centre_y + height // 2
if(left < 0 or up < 0 or right >= padded_img.shape[1] or down >= padded_img.shape[1] ):
''' for debugging
print("Neighbourhood error")
print("Neighbourhood")
print(left,right,up,down)
print("Shapes")
print(padded_img.shape,img.shape,height,width)
print("Centre : {0},{1}".format(centre_y,centre_x))
print("New Centre : {0},{1}".format(new_centre_y,new_centre_x))
print("Done")
'''
print("Invalid indexes for computing neighbourhood")
return padded_img[up : down + 1,left : right + 1]
elif np.ndim(img) == 3:
(l,b,h) = img.shape
pad_x = width // 2
pad_y = height // 2
padded_img = pad_image(img,pad_x,pad_y)
left = new_centre_x - width // 2
right = new_centre_x + width // 2
up = new_centre_y - height // 2
down = new_centre_y + height // 2
if(left < 0 or up < 0 or right >= padded_img.shape[1] or down >= padded_img.shape[1] ):
''' for debugging
print("Neighbourhood error")
print("Neighbourhood")
print(left,right,up,down)
print("Shapes")
print(padded_img.shape,img.shape,height,width)
print("Centre : {0},{1}".format(centre_y,centre_x))
print("New Centre : {0},{1}".format(new_centre_y,new_centre_x))
print("Done")
'''
print("Invalid indexes for computing neighbourhood")
return padded_img[up : down + 1,left : right + 1,:]
f0,f1,f2,tm = load_images(1)
print(f0.shape)
(573, 943, 3)
#clusters the neighbourhood around a location and tries to compute the mean and convariance for each
def getMeanandCovariance(pixels,kernel,num_cluster = 5):
#print("MEAN ")
#print(pixels.shape)
#shape of the pixels is (N,3) where N is the valid foreground/background pixels
means = []
Covs = []
clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels)
labels = np.array(clusters.predict(pixels))
for i in range(num_cluster):
group = (labels == i) #truth array of the pixels withing the cluster
this_pixels = np.asarray(pixels[group]) #pixel values of the cluster
kernel_bin = np.reshape(kernel[group], (kernel[group].size,1)) #reshape the weights to the this_pixel
kernel_sqrt = np.sqrt(kernel_bin) # useful for covariance computing
#compute the weighted mean
#compute the mean for each channel individually
meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
np.dot(this_pixels[:,2], kernel_bin)])/np.sum(kernel_bin)
#print("mean shape : {0} this_pixels shape : {1} kernel_bin.shape : {2}".format(meanbin.shape,this_pixels.shape,kernel_bin.shape))
meanbin = np.reshape(meanbin, (3,))
means.append(meanbin)
diff = (this_pixels - meanbin)
diff = np.multiply(kernel_sqrt, diff)
covbin = np.eye(3)
with np.errstate(divide='raise'): # raise errors, but dont stop execution when low number of clusters, and other cases
try:
covbin = np.dot(diff.T, diff)/(np.sum(kernel_bin) + 0.00001) + np.eye(3)*(10**(-5)) #adding small value to prevent singular matrices
except Exception as e:
print("Error")
print(covbin.shape)
#print("Maybe")
#print(covbin)
Covs.append(covbin)
means = np.array(means).T
Covs = np.array(cv2.merge(Covs)) #merge 3 channels to 1
#means have shape (3,K) K is the number of cluster
#Covs have the shape (3,3,K) where K is the number of cluster
#print(means.shape,Covs.shape,num_cluster)
return means, Covs
'''
Solves the matting Equations Iteratively
Choose the best pair of (FG,BG) which maximizes the likelyhood of a given F,B,alpha
returns the value of F,B, alpha
'''
def Solver(f0mean, f0Cov, bgmean, bgCov, f1mean, f1Cov, fmean, lmean, CCov, initial_alpha, minLikelihoodDelta = 10**(-3),maxIterations = 50):
#means have shape (3,K) K is the number of cluster
#Covs have the shape (3,3,K) where K is the number of cluster
#CMean is a [a,b,c]
#CCov is a scaler
#initial_Alpha is a float
#Some global required constants
z,num_cluster = f0mean.shape
solved_f0 = np.zeros(3)
solved_bg = np.zeros(3)
solved_f1 = np.zeros(3)
solved_alpha = 0
I = np.eye(3)
Z = np.zeros((3,3))
nIterations = 0
maxLikelihood = - np.inf
for i in range(num_cluster):
try:
invCovF0 = np.linalg.inv(f0Cov[:,:,i]) # compute inverse of the FG convariance matrix
except Exception as e: # maynot be singular
print("The Foreground matrix is not singular,Skipping for now")
continue
cur_f0mean = f0mean[:, i] #mean of ith FG Cluster 1*3
for j in range(num_cluster):
try:
invCovF1 = np.linalg.inv(f1Cov[:,:,j]) # compute inverse of the FG convariance matrix
except Exception as e: # maynot be singular
print("The Foreground Flash matrix is not singular,Skipping for now")
continue
cur_f1mean = f1mean[:, j] #mean of ith FG Cluster 1*3
for k in range(num_cluster):
try:
invCovB = np.linalg.inv(bgCov[:,:,k]) # compute inverse of the BG convariance matrix
except Exception as e: # Sometimes its singular, so we dump the matrix and skip for now!
print("The Background matrix is not singular,Skipping for now")
continue
cur_bgmean = bgmean[:, k] #mean of ith BG Cluster
#Initialization for the iterative solver
alpha = initial_alpha
nIterations = 0
prevLikelihood = -np.inf
while True:
nIterations += 1
#SOLVE THE EQUATION DESCRIBED IN THE PAPER
#define A
a11 = invCovF0 + I*(alpha/CCov)**2 #3X3
a12 = I*(alpha*(1-alpha)*(CCov)**2) # 3X3
a13 = Z
a22 = invCovB + I*((1 - alpha)/CCov)**2 #3X3
a33 = invCovF1 + I*(alpha/CCov)**2
r1 = np.hstack((a11, a12, a13)) #create the top row 3*9
r2 = np.hstack((a12, a22, a13)) # create the middle row 3*9
r3 = np.hstack((a13, a13, a33)) #create the bottom row
A = np.vstack((r1, r2, r3)) #create the final matrix 6*6
#define b
b11 = np.dot(invCovF0, cur_f0mean) + fmean*(alpha/CCov**2) # 3*1
b12 = np.dot(invCovB, cur_bgmean) + fmean*(1-alpha)/(CCov**2) # 3*1
b13 = np.dot(invCovF1, cur_f1mean) + lmean*(alpha/CCov**2) #3*2
b = np.concatenate((b11, b12, b13)).T #(6,)
#solve Ax = b
try:
#print(np.sum(A))
#print(np.sum(b))
'''
print("printing A")
for i1 in range(A.shape[0]):for j2 in range(b.shape[0]):
print("index {0} : {1}".format(j2,b[j2]))
for j1 in range(A.shape[1]):
print("index {0},{1} : {2}".format(i1,j1,A[i1,j1]))
print("printing B")
for j2 in range(b.shape[0]):
print("index {0} : {1}".format(j2,b[j2]))
'''
x = np.linalg.solve(A, b)
except Exception as e: # Sometimes there is an issue with solving if A is non invertible. This did not occur after singular matrices were skipped, but is still there for safety.
print("ERROR SOLVING")
print(e)
break
#assign f0,f1 and bg that are solved
f0Col = x[0:3]
bgCol = x[3:6]
f1Col = x[6:9]
# SOLVE FOR ALPHA using estimated F, B, C
#print("f0Col : {0} bgCol : {1} fmean : {2} lmean : {3} f1col : {4}".
# format(f0Col.shape,bgCol.shape,fmean.shape,lmean.shape,f1Col.shape))
num = np.dot((f0Col - bgCol).T, (fmean.T - bgCol)) + np.dot(f1Col.T,lmean)
den = np.dot((f0Col - bgCol).T, (f0Col - bgCol)) + np.dot(f1Col.T,f0Col)
#print(num/den)
alpha = num / den
#clip Alpha
if alpha < 0:
alpha = 0
if alpha > 1:
alpha = 1
# Compute Likelyhood
#L[0] = -np.sum((Cmean.T - alpha*fgCol - (1-alpha)*bgCol)**2)/(colCov**2) # L(C|F,B, alpha)
L1 = -(np.linalg.norm((fmean.T - alpha*f0Col - (1-alpha)*bgCol),2)**2)/(CCov**2) # L(C|F,B, alpha)
L2 = -(np.linalg.norm((lmean.T - alpha*f1Col),2)**2)/(CCov**2) # L(I'|F,, alpha)
LF0 = -(np.dot(np.dot((f0Col - cur_f0mean.T).T, invCovF0), (f0Col - cur_f0mean.T).T)/2) #L(F)
LF1 = -(np.dot(np.dot((f1Col - cur_f1mean.T).T, invCovF1), (f1Col - cur_f1mean.T).T)/2) #L(F)
LB = -(np.dot(np.dot((bgCol - cur_bgmean.T).T, invCovB), (bgCol - cur_bgmean.T).T)/2) #L(B)
L = np.array([L1,L2,LF0,LF1,LB])
likelihood = np.sum(L)
if likelihood > maxLikelihood: # If best likelihood so far, use that
solved_alpha = alpha
maxLikelihood = likelihood
solved_f0 = f0Col
solved_f1 = f1Col
solved_bg = bgCol
# Stop solving if the solver saturates or if it exceeds the maximum number of iterations per cluster pair
if abs(prevLikelihood - likelihood) < minLikelihoodDelta or nIterations > maxIterations: # Stop solving
break
prevLikelihood = likelihood
return solved_f0, solved_f1 ,solved_bg, solved_alpha
#the main function,has responsible to process the whole Joint Bayesian Matting Algorith
# f0 is the RGB no flash image
# f1 is the RGB flash image
# f2 is the RGB only flash image given by f2 = f1 - f0
# trimap is the trimap generated by our code.
# threshold is the number of known pixels in the neighbourhood for to proceed with solving
def solve(f0,f1,f2,tm,thresh = 10):
#print(f0.shape,f1.shape,f2.shape,tm.shape)
# get the regions for each type
bg,fg,unk = get_maps(tm)
y,x = np.where(unk != 0) # locations where classification is unknown
unsolved_loc = list(set(zip(y,x)))
unsolved_loc = sorted(unsolved_loc,key = lambda x : x[0]) #top to bottom
# this is essentially the alpha matrix
# 1 for foreground pixels
# 0 for background pixels
# nan for unknowns.
mask = np.copy(unk).astype(np.float64)
mask[unk != 0] = np.nan #replace unknown regions with nan
mask[fg != 0] = 1 #replace foreground region with 1
#convert fg to RGB
fg1 = np.zeros((f0.shape))
fg1[:,:,0] = fg
fg1[:,:,1] = fg
fg1[:,:,2] = fg
#convert bg to RGB for bitwise operations
bg1 = np.zeros((f0.shape))
bg1[:,:,0] = bg
bg1[:,:,1] = bg
bg1[:,:,2] = bg
#convert fg to RGB for bitwise
fg2 = np.zeros(f1.shape)
fg2[:,:,0] = fg
fg2[:,:,1] = fg
fg2[:,:,2] = fg
#generate surely background and surely foreground images
f = cv2.bitwise_and(fg1.astype(np.uint8),f0.astype(np.uint8))
b = cv2.bitwise_and(bg1.astype(np.uint8),f0.astype(np.uint8))
l = cv2.bitwise_and(fg2.astype(np.uint8),f2.astype(np.uint8))
#display_images([f,b,im],["foreground","background","original"],3,1)
iteration = 0
solved = []
tosolve = np.copy(unsolved_loc)
pass_num = 0
pass_thresh = 5 # after this threshold,window size need to be increased
window_size = 15 # neighbourhood is (19,19)
sigma = 10
print("Unsolve : {0}".format(len(unsolved_loc)))
while(len(tosolve) > 0):
pass_num += 1
tosolve = []
#create a list of locations to be solved
for loc in unsolved_loc :
#check it is not already solved
if loc not in solved:
tosolve.append(loc)
if pass_num > pass_thresh and pass_num % 3:
window_size += 2 #initally odd,remains odd.Window size increases when too many unknowns
print("PASS NUMBER : {0} , WINDOW SIZE : {1}".format(pass_num,window_size))
for loc in tosolve:
gaussian_kernel = create_gaussian(window_size,sigma) #create kernel
alpha = get_neighbourhood(mask,loc[0],loc[1],window_size,window_size)
#find fg pixels for clustering non flash
kernel_f0 = np.multiply(np.square(alpha),gaussian_kernel)
f0_window = get_neighbourhood(f,loc[0],loc[1],window_size,window_size)
known = np.nan_to_num(kernel_f0) > 0 #return a boolean array with true values for non-zero and non-nan values
f0_pixel = f0_window[known] #extract the selected pixel location
kernel_f0 = kernel_f0[known] # extract the selected pixel location
#find fg pixels for clustering flash
kernel_f1 = np.multiply(np.square(alpha),gaussian_kernel)
f1_window = get_neighbourhood(l,loc[0],loc[1],window_size,window_size)
known = np.nan_to_num(kernel_f1) > 0 #return a boolean array with true values for non-zero and non-nan values
f1_pixel = f1_window[known] #extract the selected pixel location
kernel_f1 = kernel_f1[known] # extract the selected pixel location
#find bg pixels for clustering
kernel_b = np.multiply(np.square(1- alpha),gaussian_kernel)
bg_window = get_neighbourhood(b,loc[0],loc[1],window_size,window_size)
known = np.nan_to_num(kernel_b) > 0 #return a boolean array with true values for non-zero and non-nan values
bg_pixel = bg_window[known] #extract the selected pixel location
kernel_b = kernel_b[known] # extract the selected pixel location
#check sufficient data to solve the proble
if(len(f0_pixel) >= thresh and len(bg_pixel) >= thresh) and len(f1_pixel):
f0mean,f0Cov = getMeanandCovariance(f0_pixel,kernel_f0,num_cluster = 3)
f1mean,f1Cov = getMeanandCovariance(f1_pixel,kernel_f1,num_cluster = 3)
bgmean,bgCov = getMeanandCovariance(bg_pixel,kernel_b,num_cluster = 3)
#observed_c
fmean = f0[loc[0],loc[1],:]
lmean = f1[loc[0],loc[1],:]
CCov = 3 #tunable parameter
#print(Cmean,CCov)
#take intial guess as mean
initial_alpha = np.nanmean(alpha)
#print(initial_alpha)
#iteratively solve!
final_f0, final_f1, final_bg , final_alpha = Solver(f0mean, f0Cov, bgmean, bgCov, f1mean, f1Cov, fmean, lmean, CCov, initial_alpha, maxIterations = 50)
#update the estimated values
#print(final_fg,final_bg,final_alpha)
mask[loc[0],loc[1]] = final_alpha
f[loc[0],loc[1],:] = np.array(final_f0)
b[loc[0],loc[1],:] = np.array(final_bg)
l[loc[0],loc[1],:] = np.array(final_f1)
solved.append(loc)
#print occasional status updates
if iteration % 50 == 0:
print("PASS : ", pass_num)
print("WINDOW SIZE = ", window_size)
print('SOLVED LOCATIONS = ', len(solved))
print('REMAINING LOCATIONS = ', len(tosolve) - len(solved))
#sad = np.sum(np.absolute((cv2.cvtColor(gt, cv2.COLOR_BGR2GRAY)/255).astype(np.float) - np.nan_to_num(mask)))
#print('SAD = ', sad)
print('---------------------------------------------')
final_alpha = cv2.cvtColor((mask*255).astype(np.uint8), cv2.COLOR_GRAY2BGR) #3 c
#showMultiImages((fg, bg, gt, alpha3channel), 'CURRENT')
iteration += 1
#sad = np.sum(np.absolute((cv2.cvtColor(gt, cv2.COLOR_BGR2GRAY )/255).astype(np.float) - np.nan_to_num(mask)))
print('SOLVER COMPLETED IN ', iteration, 'ITERATIONS')
print('---------------------------------------------')
print('---------------------------------------------')
print('---------------------------------------------')
return f, b, l,mask
def scale(im,sc):
return cv2.resize(np.copy(im),(0,0),fx = sc,fy = sc)
def run(index):
import time
t1 = time.time()
f0,f1,f2,tm = load_images(index)
f0 = scale(np.copy(f0),0.5)
f1 = scale(np.copy(f1),0.5)
f2 = scale(np.copy(f2),0.5)
tm = scale(np.copy(tm),0.5)
f,b,l,mask = solve(f0,f1,f2,tm,thresh = 10)
t2 = time.time()
print("Time taken : {0}".format(t2 -t1))
return f,b,l,mask
f,b,l,mask = run(1)
display_images([f,b,l],["non flash foreground","background","flash foregroun"],3,1)
Unsolve : 6065 PASS NUMBER : 1 , WINDOW SIZE : 15 PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1 REMAINING LOCATIONS = 6064 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 51 REMAINING LOCATIONS = 6014 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 101 REMAINING LOCATIONS = 5964 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 151 REMAINING LOCATIONS = 5914 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 201 REMAINING LOCATIONS = 5864 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 251 REMAINING LOCATIONS = 5814 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 301 REMAINING LOCATIONS = 5764 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 351 REMAINING LOCATIONS = 5714 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 401 REMAINING LOCATIONS = 5664 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 451 REMAINING LOCATIONS = 5614 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 501 REMAINING LOCATIONS = 5564 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 551 REMAINING LOCATIONS = 5514 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 601 REMAINING LOCATIONS = 5464 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 651 REMAINING LOCATIONS = 5414 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 701 REMAINING LOCATIONS = 5364 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 751 REMAINING LOCATIONS = 5314 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 801 REMAINING LOCATIONS = 5264 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 851 REMAINING LOCATIONS = 5214 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 901 REMAINING LOCATIONS = 5164 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 951 REMAINING LOCATIONS = 5114 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1001 REMAINING LOCATIONS = 5064 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1051 REMAINING LOCATIONS = 5014 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1101 REMAINING LOCATIONS = 4964 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1151 REMAINING LOCATIONS = 4914 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1201 REMAINING LOCATIONS = 4864 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1251 REMAINING LOCATIONS = 4814 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1301 REMAINING LOCATIONS = 4764 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1351 REMAINING LOCATIONS = 4714 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1401 REMAINING LOCATIONS = 4664 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1451 REMAINING LOCATIONS = 4614 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1501 REMAINING LOCATIONS = 4564 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1551 REMAINING LOCATIONS = 4514 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1601 REMAINING LOCATIONS = 4464 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1651 REMAINING LOCATIONS = 4414 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1701 REMAINING LOCATIONS = 4364 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1751 REMAINING LOCATIONS = 4314 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1801 REMAINING LOCATIONS = 4264 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1851 REMAINING LOCATIONS = 4214 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1901 REMAINING LOCATIONS = 4164 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 1951 REMAINING LOCATIONS = 4114 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2001 REMAINING LOCATIONS = 4064 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2051 REMAINING LOCATIONS = 4014 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2101 REMAINING LOCATIONS = 3964 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2151 REMAINING LOCATIONS = 3914 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2201 REMAINING LOCATIONS = 3864 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2251 REMAINING LOCATIONS = 3814 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2301 REMAINING LOCATIONS = 3764 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2351 REMAINING LOCATIONS = 3714 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2401 REMAINING LOCATIONS = 3664 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2451 REMAINING LOCATIONS = 3614 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2501 REMAINING LOCATIONS = 3564 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2551 REMAINING LOCATIONS = 3514 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2601 REMAINING LOCATIONS = 3464 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2651 REMAINING LOCATIONS = 3414 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2701 REMAINING LOCATIONS = 3364 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2751 REMAINING LOCATIONS = 3314 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2801 REMAINING LOCATIONS = 3264 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2851 REMAINING LOCATIONS = 3214 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2901 REMAINING LOCATIONS = 3164 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 2951 REMAINING LOCATIONS = 3114 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3001 REMAINING LOCATIONS = 3064 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3051 REMAINING LOCATIONS = 3014 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3101 REMAINING LOCATIONS = 2964 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3151 REMAINING LOCATIONS = 2914 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3201 REMAINING LOCATIONS = 2864 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3251 REMAINING LOCATIONS = 2814 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3301 REMAINING LOCATIONS = 2764 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3351 REMAINING LOCATIONS = 2714 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3401 REMAINING LOCATIONS = 2664 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3451 REMAINING LOCATIONS = 2614 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3501 REMAINING LOCATIONS = 2564 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3551 REMAINING LOCATIONS = 2514 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3601 REMAINING LOCATIONS = 2464 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3651 REMAINING LOCATIONS = 2414 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3701 REMAINING LOCATIONS = 2364 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3751 REMAINING LOCATIONS = 2314 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3801 REMAINING LOCATIONS = 2264 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3851 REMAINING LOCATIONS = 2214 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3901 REMAINING LOCATIONS = 2164 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 3951 REMAINING LOCATIONS = 2114 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4001 REMAINING LOCATIONS = 2064 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4051 REMAINING LOCATIONS = 2014 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4101 REMAINING LOCATIONS = 1964 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4151 REMAINING LOCATIONS = 1914 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4201 REMAINING LOCATIONS = 1864 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4251 REMAINING LOCATIONS = 1814 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4301 REMAINING LOCATIONS = 1764 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4351 REMAINING LOCATIONS = 1714 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4401 REMAINING LOCATIONS = 1664 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4451 REMAINING LOCATIONS = 1614 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4501 REMAINING LOCATIONS = 1564 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4551 REMAINING LOCATIONS = 1514 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4601 REMAINING LOCATIONS = 1464 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4651 REMAINING LOCATIONS = 1414 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4701 REMAINING LOCATIONS = 1364 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4751 REMAINING LOCATIONS = 1314 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4801 REMAINING LOCATIONS = 1264 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4851 REMAINING LOCATIONS = 1214 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4901 REMAINING LOCATIONS = 1164 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 4951 REMAINING LOCATIONS = 1114 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5001 REMAINING LOCATIONS = 1064 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5051 REMAINING LOCATIONS = 1014 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5101 REMAINING LOCATIONS = 964 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5151 REMAINING LOCATIONS = 914 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5201 REMAINING LOCATIONS = 864 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5251 REMAINING LOCATIONS = 814 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5301 REMAINING LOCATIONS = 764 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5351 REMAINING LOCATIONS = 714 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5401 REMAINING LOCATIONS = 664 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (2) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5451 REMAINING LOCATIONS = 614 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5501 REMAINING LOCATIONS = 564 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin), <ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5551 REMAINING LOCATIONS = 514 ---------------------------------------------
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (3) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5601 REMAINING LOCATIONS = 464 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5651 REMAINING LOCATIONS = 414 --------------------------------------------- PASS : 1 WINDOW SIZE = 15 SOLVED LOCATIONS = 5701 REMAINING LOCATIONS = 364 --------------------------------------------- PASS NUMBER : 2 , WINDOW SIZE : 15 PASS : 2 WINDOW SIZE = 15 SOLVED LOCATIONS = 5751 REMAINING LOCATIONS = -5422 --------------------------------------------- PASS : 2 WINDOW SIZE = 15 SOLVED LOCATIONS = 5801 REMAINING LOCATIONS = -5472 --------------------------------------------- PASS : 2 WINDOW SIZE = 15 SOLVED LOCATIONS = 5851 REMAINING LOCATIONS = -5522 --------------------------------------------- PASS : 2 WINDOW SIZE = 15 SOLVED LOCATIONS = 5901 REMAINING LOCATIONS = -5572 --------------------------------------------- PASS : 2 WINDOW SIZE = 15 SOLVED LOCATIONS = 5951 REMAINING LOCATIONS = -5622 --------------------------------------------- PASS : 2 WINDOW SIZE = 15 SOLVED LOCATIONS = 6001 REMAINING LOCATIONS = -5672 --------------------------------------------- PASS NUMBER : 3 , WINDOW SIZE : 15
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (4) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS NUMBER : 4 , WINDOW SIZE : 15 PASS : 4 WINDOW SIZE = 15 SOLVED LOCATIONS = 6051 REMAINING LOCATIONS = -6036 --------------------------------------------- PASS NUMBER : 5 , WINDOW SIZE : 15 PASS NUMBER : 6 , WINDOW SIZE : 15 PASS NUMBER : 7 , WINDOW SIZE : 17 PASS NUMBER : 8 , WINDOW SIZE : 19 PASS NUMBER : 9 , WINDOW SIZE : 19 PASS NUMBER : 10 , WINDOW SIZE : 21 PASS NUMBER : 11 , WINDOW SIZE : 23 PASS NUMBER : 12 , WINDOW SIZE : 23 PASS NUMBER : 13 , WINDOW SIZE : 25 PASS NUMBER : 14 , WINDOW SIZE : 27 PASS NUMBER : 15 , WINDOW SIZE : 27 PASS NUMBER : 16 , WINDOW SIZE : 29 PASS NUMBER : 17 , WINDOW SIZE : 31 PASS NUMBER : 18 , WINDOW SIZE : 31 PASS NUMBER : 19 , WINDOW SIZE : 33 PASS NUMBER : 20 , WINDOW SIZE : 35 PASS NUMBER : 21 , WINDOW SIZE : 35 PASS NUMBER : 22 , WINDOW SIZE : 37 PASS NUMBER : 23 , WINDOW SIZE : 39 PASS NUMBER : 24 , WINDOW SIZE : 39 PASS NUMBER : 25 , WINDOW SIZE : 41 PASS NUMBER : 26 , WINDOW SIZE : 43 PASS NUMBER : 27 , WINDOW SIZE : 43 PASS NUMBER : 28 , WINDOW SIZE : 45 PASS NUMBER : 29 , WINDOW SIZE : 47 PASS NUMBER : 30 , WINDOW SIZE : 47 PASS NUMBER : 31 , WINDOW SIZE : 49 PASS NUMBER : 32 , WINDOW SIZE : 51 PASS NUMBER : 33 , WINDOW SIZE : 51 PASS NUMBER : 34 , WINDOW SIZE : 53 PASS NUMBER : 35 , WINDOW SIZE : 55 PASS NUMBER : 36 , WINDOW SIZE : 55 PASS NUMBER : 37 , WINDOW SIZE : 57 PASS NUMBER : 38 , WINDOW SIZE : 59 PASS NUMBER : 39 , WINDOW SIZE : 59 PASS NUMBER : 40 , WINDOW SIZE : 61 PASS NUMBER : 41 , WINDOW SIZE : 63 PASS NUMBER : 42 , WINDOW SIZE : 63 PASS NUMBER : 43 , WINDOW SIZE : 65 PASS NUMBER : 44 , WINDOW SIZE : 67 PASS NUMBER : 45 , WINDOW SIZE : 67 PASS NUMBER : 46 , WINDOW SIZE : 69 PASS NUMBER : 47 , WINDOW SIZE : 71 PASS NUMBER : 48 , WINDOW SIZE : 71 PASS NUMBER : 49 , WINDOW SIZE : 73 PASS NUMBER : 50 , WINDOW SIZE : 75 PASS NUMBER : 51 , WINDOW SIZE : 75 PASS NUMBER : 52 , WINDOW SIZE : 77 PASS NUMBER : 53 , WINDOW SIZE : 79 PASS NUMBER : 54 , WINDOW SIZE : 79 PASS NUMBER : 55 , WINDOW SIZE : 81 PASS NUMBER : 56 , WINDOW SIZE : 83 PASS NUMBER : 57 , WINDOW SIZE : 83 PASS NUMBER : 58 , WINDOW SIZE : 85 PASS NUMBER : 59 , WINDOW SIZE : 87 PASS NUMBER : 60 , WINDOW SIZE : 87 PASS NUMBER : 61 , WINDOW SIZE : 89 PASS NUMBER : 62 , WINDOW SIZE : 91 PASS NUMBER : 63 , WINDOW SIZE : 91 PASS NUMBER : 64 , WINDOW SIZE : 93 PASS NUMBER : 65 , WINDOW SIZE : 95 PASS NUMBER : 66 , WINDOW SIZE : 95 PASS NUMBER : 67 , WINDOW SIZE : 97 PASS NUMBER : 68 , WINDOW SIZE : 99
<ipython-input-27-ede0654d1681>:9: ConvergenceWarning: Number of distinct clusters (1) found smaller than n_clusters (5). Possibly due to duplicate points in X. clusters = KMeans(n_init = 5, n_clusters = num_cluster , random_state = 0).fit(pixels) <ipython-input-27-ede0654d1681>:19: RuntimeWarning: invalid value encountered in true_divide meanbin = np.array([np.dot(this_pixels[:,0], kernel_bin),np.dot(this_pixels[:,1], kernel_bin),
PASS NUMBER : 69 , WINDOW SIZE : 99 SOLVER COMPLETED IN 6065 ITERATIONS --------------------------------------------- --------------------------------------------- ---------------------------------------------
np.unique(mask)
array([0. , 0.78136151, 0.78361439, 0.81567336, 0.81842579,
0.82816523, 0.82930855, 0.8370937 , 0.83833196, 0.84654254,
0.8516133 , 0.85555014, 0.86102867, 0.86269305, 0.86407806,
0.89236169, 0.90015179, 0.90365709, 0.90366519, 0.91595168,
0.93285823, 0.93549314, 0.93552378, 0.93764044, 0.95073973,
0.9515216 , 0.9572191 , 0.97248966, 0.97313811, 0.97555714,
0.99097726, 0.99153465, 1. ])
f0 = scale(np.copy(f0),0.5)
plt.imshow(f0)
<matplotlib.image.AxesImage at 0x7f5f01646ee0>
f0 = scale(np.copy(f0),0.5)
final_image = np.copy(f0)
for i in range(mask.shape[0]):
for j in range(mask.shape[1]):
if(mask[i,j] <= 0.75):
final_image[i,j,:] = 0
plt.imshow(final_image)
<matplotlib.image.AxesImage at 0x7f5f01e653a0>